Consistency of interictal and ictal onset localization using magnetoencephalography in patients with partial epilepsy
Bibliographic record
Abstract
OBJECT: The aim of this study was to evaluate the spatial accuracy of interictal magnetoencephalography (MEG) in localizing the primary epileptogenic focus in comparison with alternative MEG-derived estimates such as ictal onset recording or sensory mapping of the periphery where seizures manifest. METHODS: During this retrospective study of 12 patients with epilepsy who had undergone successful magnetic source (MS) imaging with the aid of a dual 37-channel biomagnetometer as well as simultaneous MEG/electroencephalography (EEG) recordings, ictal events were observed in five patients and quantitative comparisons of interictal spike and ictal seizure onset source localizations were made. In the eight patients who had presented with sensorimotor seizure, source localization of cortical sites concordant with seizure foci was determined using somatosensory functional mapping, and the results were quantitatively compared with interictal spike source localizations. Interictal spike sources demonstrated on MEG localized to the same region as the corresponding ictal event or somatosensory source localizations. The mean distance between the ictal foci and interictal spike sources was 1.1 +/- 0.3 cm. Results of functional somatosensory mapping in patients with sensorimotor seizures demonstrated that seizure sources consistently colocalized with interictal MEG spike sources, with a mean distance of 1.5 +/- 0.4 cm. No systematic directional bias was observed. Interictal sources tended to be tightly clustered, and the mean ellipsoid volume, defined by one standard deviation of the source spatial coordinates, was 1 cm3. CONCLUSIONS: Interictal spike localizations on MEG were concordant with ictal and, where relevant, functional somatosensory mapping localizations. These findings support the interpretation of interictal spikes on MEG as a useful and effective noninvasive method for localizing primary seizure foci.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".